Update README.md

README.md

@@ -12,10 +12,10 @@ The model almost achieves SOTA results while being 20x smaller, on a test set co
 
 | **Model** | **Precision** | **Recall** | **F1-score** | **F2-score** |
 | :-------- | :------------ | :--------- | :----------- | :----------- |
-| [`alexandrainst/danoff-base`](https://huggingface.co/alexandrainst/danoff-base) | 74.81% | **89.77%** | **81.61%** | **86.32%** |
-| `alexandrainst/danoff-small` (this) | 74.13% | 89.30% | 81.01% | 85.79% |
+| [`alexandrainst/da-offensive-detection-base`](https://huggingface.co/alexandrainst/danoff-base) | 74.81% | **89.77%** | **81.61%** | **86.32%** |
+| `alexandrainst/da-offensive-detection-small` (this) | 74.13% | 89.30% | 81.01% | 85.79% |
 | [`A&ttack`](https://github.com/ogtal/A-ttack) | **97.32%** | 50.70% | 66.67% | 56.07% |
-| [`alexandrainst/da-electra-hatespeech-detection`](https://huggingface.co/alexandrainst/da-electra-hatespeech-detection) | 86.43% | 56.28% | 68.17% | 60.50% |
+| [`alexandrainst/da-hatespeech-detection-small`](https://huggingface.co/alexandrainst/da-hatespeech-detection-small) | 86.43% | 56.28% | 68.17% | 60.50% |
 | [`Guscode/DKbert-hatespeech-detection`](https://huggingface.co/Guscode/DKbert-hatespeech-detection) | 75.41% | 42.79% | 54.60% | 46.84% |
 
 
@@ -25,7 +25,7 @@ You can use the model simply by running the following:
 
 ```python
 >>> from transformers import pipeline
->>> offensive_text_pipeline = pipeline(model="alexandrainst/danoff-small")
+>>> offensive_text_pipeline = pipeline(model="alexandrainst/da-offensive-detection-small")
 >>> offensive_text_pipeline("Din store idiot")
 [{'label': 'Offensive', 'score': 0.9997463822364807}]
 ```